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AI tools can aid in streamlining training plans. It helps in building learning objectives, streamlining research, creating assessments, providing feedback, and improving writing quality. Collaboration is boosted with tools like Microsoft Copilot.

Units in this learning path:

• Introduction
• Use AI for Training Plans
• AI Support for Content Creation
• Enhance Training Plans with Microsoft 365 Copilot
• Enhance Meetings Remote Training Environments
• Use AI Tools to Build Assessments
• Use Generative AI Self Evaluation
• Knowledge Check
• Summary

Products: AI Services, Azure Machine Learning, Azure Machine Learning Designer, M365 Apps, Azure Translator Text, Azure Translator Speech, Ms Copilot, Language Service

Roles: K 12 Educator, Business User, Higher Ed Educator, Data Engineer, School Leader

Level: Beginner

Subjects: Artificial Intelligence

Duration: 18 minutes

Learn to summarize data with Foundry Tools and Azure database for PostgreSQL.

Units in this learning path:

• Introduction
• Explain Extractive Summarization
• Explore Abstractive Summarization
• Exercise Perform Extractive Abstractive Summarization
• Knowledge Check
• Summary

Products: Azure Database Postgresql, AI Services

Roles: Developer

Level: Intermediate

Subjects: Artificial Intelligence, Databases

Duration: 21 minutes

Learn to use AI tools to simplify and translate educational communications, ensuring inclusivity and accessibility for diverse families.

Units in this learning path:

• Introduction
• Translate Simplify Written Communication
• Make Live Meetings Accessible
• Offer Flexible Engagement Options
• Reflection Exercise
• Knowledge Check
• Summary

Products: M365, Microsoft 365 Copilot, Office Teams, Office Powerpoint, Office Word

Roles: K 12 Educator, School Leader

Level: Beginner

Subjects: Artificial Intelligence, Generative AI

Duration: 21 minutes

This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey. We are aware some…

This module explores the dynamic integration of artificial intelligence (AI) in education.

Units in this learning path:

• Introduction
• Integrate Artificial Intelligence Education
• AI and Future of Education
• Knowledge Check
• Summary

Products: AI Services, Azure Machine Learning, Azure Machine Learning Designer, M365 Apps, Azure Translator Text, Azure Translator Speech, Ms Copilot, Language Service

Roles: K 12 Educator, Higher Ed Educator, Business User, Data Engineer, School Leader

Level: Beginner

Subjects: Artificial Intelligence

Duration: 17 minutes

Explore how Azure OpenAI Studio enables the development of AI-powered dialogue systems. Learn the core architecture of conversational agents, the models behind them, and how to design basic chat interactions using Microsoft tools.

Units in this learning path:

• Introduction
• AI Powered Dialogue Systems
• Components and Architecture of Dialogue Systems
• Overview of AI Models Used in Dialogue Systems
• Azure Openai Studio Overview
• Exercise
• Knowledge Check
• Summary

Products: Ms Copilot, Azure Openai

Roles: Data Engineer, Data Scientist, Developer

Level: Beginner

Subjects: Artificial Intelligence

Duration: 75 minutes

This Playlist is an unordered collection of supplemental labs that have relevance to the classroom training The Machine Learning Pipeline on AWS. Students of that class may find the labs in this playlist to be useful hands-on practice.

This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey. We are aware some…

Learn how to use MLflow for model tracking when experimenting in notebooks.

Units in this learning path:

• Introduction
• Use Mlflow Model Tracking
• Train Models Notebooks
• Exercise Track Model Training
• Knowledge Check
• Summary

Products: Azure Machine Learning

Roles: Data Scientist

Level: Beginner

Subjects: Machine Learning

Duration: 33 minutes

Learn how to track model training with MLflow in jobs when running scripts.

Units in this learning path:

• Introduction
• Track Metrics Mlflow
• View Metrics Evaluate Models
• Exercise Use Mlflow Track Training Jobs
• Knowledge Check
• Summary

Products: Azure Machine Learning

Roles: Data Scientist

Level: Beginner

Subjects: Machine Learning

Duration: 34 minutes

Train and evaluate classification models

Units in this learning path:

• Introduction
• What Is Classification
• Exercise Model
• Evaluate Classification Models
• Exercise Alternative Classification Metrics
• Multiclass Classification
• Exercise Multiclass Classification
• Knowledge Check
• Summary

Products: Azure

Roles: Data Scientist

Level: Intermediate

Subjects: Machine Learning, Classification Analysis

Duration: 64 minutes

Clustering is a type of machine learning that is used to group similar items into clusters.

Units in this learning path:

• Introduction
• What Is Clustering
• Exercise Model
• Different Types Clustering
• Exercise New Models
• Knowledge Check
• Summary

Products: Azure

Roles: Data Scientist

Level: Intermediate

Subjects: Machine Learning

Duration: 46 minutes